Embodiments of the invention relate generally to magnetic resonance (MR) imaging and, more particularly, to a system and method for MR image scan and analysis.
When a substance such as human tissue is subjected to a uniform magnetic field (polarizing field B0), the individual magnetic moments of the spins in the tissue attempt to align with this polarizing field, but precess about it in random order at their characteristic Larmor frequency. If the substance, or tissue, is subjected to a magnetic field (excitation field B1) which is in the x-y plane and which is near the Larmor frequency, the net aligned moment, or “longitudinal magnetization”, MZ, may be rotated, or “tipped”, into the x-y plane to produce a net transverse magnetic moment Mt. A signal is emitted by the excited spins after the excitation signal B1 is terminated and this signal may be received and processed to form an image.
When utilizing these signals to produce images, magnetic field gradients (Gx, Gy, and Gz) are employed. Typically, the region to be imaged is scanned by a sequence of measurement cycles in which these gradients vary according to the particular localization method being used. The resulting set of received NMR signals are digitized and processed to reconstruct the image using one of many well known reconstruction techniques.
Conventional MR imaging typically follows a prescribe-ahead imaging model that outputs, for example, diagnostic images formed of different pixel intensities. In the prescribe-ahead model, one or more MR scanning protocols based on a desired imaging study are typically chosen and implemented by a technician. One or more images are then generated, and the technician or a doctor analyzes or “reads” the image(s) and determines if any anomalies are evident in the image(s) and also determines if further scanning is needed. If further scanning is needed, the technician and/or doctor determine if the same scanning protocol will be implemented and/or if one or more different scanning protocols will be implemented. Often, a technician and/or doctor undergoes several iterations of the scanning and reading procedure until a proper diagnosis can be made or until it is determined that no anomalies are present in the imaged region.
The “reading” of MR images and the prescription of scanning protocols, however, typically requires a special skill set and can often be a time consuming and costly process. Generally, a skilled technician and/or doctor is needed to undertake an MR study.
In a study where several different sections of the anatomy are scanned, such as in a whole-body screening study, the scan parameters need to be adjusted to fit the specific region of the body. For example, a scan for the head generally requires a different technique (and acquisition parameters) than that for the lower abdomen. Hence, the skilled technician and/or doctor generally needs to manually adjust for the type of scan, spatial coverage, and acquisition parameters or protocols for each region of the body. This can be a time-consuming process.
It would therefore be desirable to have a system and method capable of automatically analyzing MR images, where the analysis identifies a section of anatomy that is scanned.